Insights into Digital Insurance

Wade Erickson (00:12):

Welcome all to another episode of Tech Leaders Unplugged. Today we're getting unplugged with Lisa Smith, CEO, and founder of Tech Insure, and we're going to talk about digital technology and how it's impacting the insurance business. So looking forward to that topic. Thank you very much, Lisa, for joining us today. Appreciate your time to share your topic and your information with our community here. And yeah, so let's go ahead and jump into who you are, a little bit about Tech Insure, and then we'll jump into the topic.

Lisa Smith (00:48):

Thank you so much for having me. This is so exciting to, to be able to share this with your audience. There's a lot happening in the insurance industry, even though as consumers, you don't get to see it yet. So how we started, I started Tech Short Consulting as a way to help the insurance industry with their technology solutions, looking at different opportunities to better their systems, how to do, how to get all their systems and processes functioning together. There really wasn't a job title for me when I was working in the industry. I grew into it. The way I would describe the way my brain works now is business architect. It's how can I use all these pieces to make your business work for you? And that role does exist now, and there's, there's lots of people out there who might be, want to research it and become business architects. It's really been exciting. Now we've taken that Tech Insure Consulting and I built behind it a team. There's a team of consultants who bill under me who work with me advising insurance companies who do the actual carrier product management, MGAs who specialize in niche carriers and the brokers and agents who do the distribution. And how do we help that whole value chain with their technology solutions fit together? And one thing we consistently found is that there's a lot of play in digitizing, taking the current processes and making them digital, getting rid of paper, getting rid. I used to go to conferences that we talk about front-end scanning versus backend scanning. And before we finally realized that it was really about paper elimination. And that's what I mean by business architecture. It's how all these pieces fit to make our business better and to come back. The problem that we kept consistently not seeing a solution for was distribution. The insurance sales side is so disintermediated from the manufacturer of our product, the insurance policies that, and there's a lot of mistrust, a lot of ambiguity, a lot of data transfer, a lot of stress in that relationship both digitally and and physically. And so we created a second company Tech Ensure Solutions. And what we've been working on is a digital front end solution that helps all these systems talk together, work together to do what we should have been doing in the first place. And that's the point I mentioned. You might not see it as a consumer buying your insurance policies today might still seem a very archaic, very heavy process, very old fashioned, but there's a lot of legwork happening in the background to fix some things so that we can make that better. And that's what we've been working on, is that front end solution to get the policies in the hands of the people who need it. And that might sound a bit irony because nobody ever, ever wants to buy insurance, right? It, it's the thing we do when we're forced to. But the reality is as the economy is so unstable right now, the one thing that insurance does is provide financial stability. It's meant to make sure that you don't suffer a financial loss because of something un fortuitous to you. And I think people need that protection more than ever right now, and more than ever though it's not available to them because of climate change, disaster funding different other issues that are going on over there. And because we can't sell it to them in a way that the modern consumer is trying to buy it. And so I'm really looking forward to this discussion to talk about those digital challenges, insurance, what we've been doing in the background to overcome it, what we want to do in the foreground to actually get those solutions in the hands of, of consumers.

Wade Erickson (04:44):

Great. Great. So so as we jump in the topic here, I know there are some AI and machine learning or some of these things that are hot topics in all kinds of areas. And so I know we're going to get into that as well as, as you know, insurance and, and finance and all kinds of areas within companies AI is, is is very much disruptive now to, to improving efficiencies of that productivity. So I know we'll jump into that. What else kind of interested you to talk about this topic part of your business obviously. And, and you know, what else was there in, in the choice of this topic that was particular you wanted to cover today?

Lisa Smith (05:31):

I can't wait to talk about AI because I think there's so much there. Certainly, definitely the opportunity to promote the business is always fabulous. It's one of my personal goals to become an insurance influencer. Just kidding. I don't know that there is such a thing, but maybe if there is, I I have a chance of being one. But I think the biggest thing that I'd love to kind of inspire your audience to see is I know you guys work with a lot of different industries, is to say, Hey, along with the fintech’s, there's a whole another subject of ins InsureTechs that you could be listening to that you could be following that are doing some really cool and interesting things. And the insurance industry is, is kind of the original big data company. You know, from the times it started back in the Lloyd's coffeehouses with the data on the ships and the sinkings and the pirate sightings and, and all of those adventures and how it came to be so that you can buy a homeowner's policy or you can buy a pet medical policy is, is all based on data driven. And if I can inspire a few people to maybe get involved, get, get us and help us on this journey and make sure that you're paying attention to see what's going on over here, it is kind of an interesting you don't always think of it as interesting, but there really is a lot of interesting things happening.

Wade Erickson (06:53):

Sure. And you know, just like any business, we are becoming more and more data driven. And like you said, you, you historically, all those risk models and all of that had to come from somewhere. They weren't guesses. And so they were based on people collecting that information. And you can imagine where there's lots of data, there's lots of room for algorithm analytics and all of that kind of stuff.

Lisa Smith (07:18):

Yeah, we're the original founders of all of that, you know, and all the data scientists came out after, but we've been using actuaries and backgrounds for hundreds of years. So it's kind of interesting as we get talking about where we have the data though, but it's also interesting I find as an industry where we don't

Wade Erickson (07:36):

Great. So when you, when you have somebody that comes to you as a prospective customer obviously they have a lot of tech already in place. They wouldn't be in business if they didn't. And then of course, you know, like most industries, some of that is aged, you know, like you said, you've been around for a long time. So it was mainframes, a lot of mainframes. And there probably still is some, you know, around because once you get settled in your ways and processing things and they're not broke, you kind of keep 'em around. What other kinds of areas are you looking at then when you when somebody comes to you and says, Hey, I need a tech refresh, what, can you help me?

Lisa Smith (08:14):

The biggest thing still is, and, and it's a bit frustrating in, in my 30 year career that I'm still talking about the same topic I was 20 years ago. You know, I spent the first 10 years establishing your self-learning your industry. But the topic is connectivity. It, it's how do we get these systems to play together? It's somebody comes up with an innovative product and an innovative way to rate it. But I needed then an innovative way to integrate with that so that I can sell it. You know? So then when I sell the policy, somebody then needs to deal with the innovative way of tracking and reporting all of that data because we are so regulated very much like fintechs. The insurance industries are highly, highly regulated. So there's stat reporting, data reporting, tracking, monitoring, all that loss ratio data has to feed back again into the actuaries to say, did you get it right? As much as I'd love for my career to say I advanced through different things, fundamentally the first thing we always seem to start with is connectivity. Are your systems talking to each other? Is the right data getting to the right place? Because you can't do anything else until you've got that part there. And we have, I don't even want to guess how much data the insurance industry is sitting on, but is it accessible? Is it in a format we can use? Is it in a, in a steady state that's reliable that we could start to talk AI ML?

Wade Erickson (09:40):

Yeah, that's obviously everybody talks about ai. If you don't have good data, if the data's dirty and stuff like that, it's not going to produce you know, the intelligent results that you're looking for. It's just going to be muddy. Just a organized mud.

Lisa Smith (09:58):

Well, it's, it's the age old data expression of garbage and garbage out, right? If you don't have the right data in, you're not going to get the right data out. So talking about the AI and ml, and let's bridge into that question a little bit with this scenario chat, GPT or copilot. Everybody's learning to interact with these models at, at a basic level. We're all trying to learn this technology and how to use it together, but fundamentally, one of the biggest frustrations I have is if you don't ask it the right question, it's fairly literal and it doesn't know how to respond. So I get told sometimes, well, you know, when you use punctuation in your text or your social media messages, it looks old fashioned, but punctuation helps define that sentence. That grammar, asking questions the wrong way will get you the wrong answer. And that's where the data scientists and the data analysts usually help cleanse that, clarify that. And while we're talking about AI ML, is it really ready to handle all of this? Some industries have really great structured data that they can layer the ML on top of and then therefore get very decent AI results. A lot of the medical research, a lot of the legal research contracting and historical precedent, they have a very great structured set of data that you can work from, that you can research from. You can tell how often a certain case has been referenced or cited. You can tell how often it's been used and, and reviewed in insurance, we don't have that each year in property and casualty. The rates are reset and refreshed based on the loss ratios. The last a hundred, 300 years of data that we've got don't really mean anything. If a car comes out with a new safety feature that now we either have to pay to fix or it starts to prevent and save lives and injuries you know, workers' comp in the us if there's a new safety rule, what's the impact on our policies and the enforceability of those rules? And how's it going to change your rates in your program? Historical data is only going to get us so far. The idea of AI and ML for predictive gets really exciting. But it's funny, as an industry, I don't know that our data is in a format we can consume it. As you mentioned, a lot of this is sitting on legacy mainframe servers. A lot of this is in contextual manuscript wordings we call them. And, and it just basically means that your insurance policy isn't a standard policy, it's custom. How do I start to normalize that kind of data so that we can do learning on it to say, these are the clauses that work, these are the clauses that didn't work. It's a really big challenge. And as I said, I'd love to be able to edit this conversation, inspire some people to come in and help us take this on. Because as good as we are with the data, we can be better.

Wade Erickson (12:58):

Right. So one thing to kind look at too is with ai, AI's good and machine learning is good with, like you said, predictive dealing with a bit more randomness of the data, you know, through these large language models. And you know, it can make assumptions on the past, but you know, if anybody's, you know, been working with these chat GPS and stuff like that, it's your expertise that you bring forward to the results to actually assess it and decide, is this something that makes sense? All they talk about hallucination, they talk about all these other things that can cause the result to not be correct. And so you know, it's, it's funny that we need to apply our own human expertise on top of the AI to make sure that the results you got back, it's just a, an expediter. It's not a hundred percent. And now with an insurance, you guys are so tight within your quantitative analysis that you don't have room for incorrectness or randomness. So you're kind of caught, you know, if you're writing a reporter, writing a document, that's one thing. Cause it can, you know, be 95, 90% accurate and it's okay, it's just a document or whatever. But within that you're talking inaccurate analysis and decisions on the risk levels can cause millions of dollars in the wrong way. And so, you know, tell me a little bit about how AI and your industry and randomness kind of plays with that.

Lisa Smith (14:33):

Well, let's look at two different scenarios from two very different angles. So a very simple one based on where we're talking right now is how can chat GPT when people are playing with it and experimenting how it can lead you astray? So as I mentioned, insurance is protection, it's financial protection. So if you simply ask, what's the average claim that I need to be protected from? And the good news is, by the way, it doesn't matter if I'm talking Canadian dollars, US dollars any other currency, the number really isn't all that different. It's about $75,000 for an auto claim is the average claim. So you're thinking then, okay, as a consumer, I need $75,000 worth of protection. And depending on what jurisdiction you live in, maybe that's what you get. But the reality is, if you ask that question of how much should I buy? Just that little rephrase of the question, the research in the background of the way the AI algorithms work, it changes it because it'll tell you then that there's state and provincial minimums. And in Canada, in most of our jurisdictions, that's $200,000 of liability that we want you to buy. So it's not just that you're going to have a $75,000 accident, but we're going to tell you that in order to drive on our streets and roads, you have to provide proof of payment, proof of ability to pay for damage that you may cause with your car $200,000. But then you go and you talk to the agents and the brokers, or because you've asked, how much should I buy instead of how much do I need to buy that again, a little grammar question, grammatical change totally changes your output. And the output becomes, well, most policies are sold in Canada as an example for 1 million or $2 million. And you're like, that's crazy. I only need $75,000 to cover the base loss. $200,000 is proof of payment for my my ability to, to drive. Why are they selling me this much? And this is the data that's not in databases. This is the data where the agent or the advisor to you knows that you have assets that may be worth more and we need to protect your assets. That's what we're actually doing. It's what if you're sued, how much protection do you need to keep you in your financial position? And that's a lot more than $75,000. For some people it may or may not be more than 200,000. But the other thing is we know the cost of issuing that policy, of doing the underwriting and the research to set that up. And honestly, the first 500, 700,000 of liability coverage and protection is the most expensive. That difference to get you up to an incremental of a million is pennies on the dollar. So if I'm going to offer you financial protection, I'm going to offer you what you need. And that's the 1 million or $2 million that comes standard. They may sell you additional protection above and beyond it if it if it's required for your financial needs, et cetera. That's the difference. And here's what's neat that not everybody may know about the insurance industry, but those advisors are held to a standard very similar to a lot of medical practitioners. Legal practitioners. They're licensed. They report to a board who has ethics to make sure that they're selling you the right amount to make sure that they're counseling you. Correct. We have errors in omissions insurance that protects us when we make a mistake if we offer you the wrong counsel, because we're offering you counsel, like an engineer, like a doctor, like a lawyer as a professional, not as a consumer off the street. It's not just some sales guy that's an educated professional that's trying to counsel you. So how you phrase this in AI in the ChatGPT you don't know how to phrase the question to necessarily get the right answer of what you're trying to do. You may not have the expertise behind that product to make sure that it's there. So how am I going to work with these systems and these solutions to make sure that if, if people are selling products digitally, that we're doing the right thing, that we're still getting to the right audience, to the right people that we're preventing fraud from happening in here? Because that drives a lot of your premiums in your rate. The second thought I different approach that I thought I would take and, and give you a different scenario on this is let's look at what's happening. It's been very public in California in particular, but it's very true in a lot of, of jurisdictions across the globe. And that is underwriting because of that historical data is based on a pool that we expect a certain number of losses. Climate change is impacting those disasters and they're more severe and they're more frequent. And those are the two things that insurance companies always look at as frequency and severity. What's happening in California and Florida is that the incumbents don't want to take on new business. They don't want to write more policies. You can't get new homeowner policies in these jurisdictions. It's true of a lot of products in a lot of areas. And the impact of that is crazy because of the way the insurance industry has evolved. And we almost need to devolve, we almost need to look at what's happening in the Asia markets, in the APAC markets and say, you're leapfrogging us. You're doing things differently. Why? Why is our model not being adopted over there? And the answers comes down to a very simple example. If you live in California right now and you can't get apartment insurance, okay, you can absorb that risk, maybe replace your couch if it's damaged or whatever. The largest claim historically in California until the recent wildfires is actually dog bites. Hmm. So dog bite insurance is actually a liability product and it's bundled into your home insurance. But if I can't sell you a tenant policy, you can't buy dog pet owner liability insurance. You can buy the medical to cover your vet bills, but you can't buy a liability policy standalone that just says, I'm protected if my dog bites somebody. So we are leaving a whole generation of people out here unprotected against a liability claim, which is possibly one of your biggest claims. Think of those stories where your pet a pet, not your pet mals a child and that child is disfigured for the rest of their, their life or has a big medical bill, an injury claim that they have to now settle. That's the kind of financial protection that we're selling you the one or 2 million for. But in California, under, in Florida, because you can't get homeowners insurance, you can't buy that protection.

Wade Erickson (21:02):

It's amazing. So the bundling, which was meant at one time to be a a way to provide additive protection. Now because the main insurance is blocked, it has no way to be split out. That's interesting. Yeah. It's cause obviously the menu of the kinds of things and the kinds of acts that are covered you in these umbrella style policies that you get within your homeowner's insurance, you know, whether it's property damage, theft, all of these things, you know, if you can't get one, like you said, apartments, I mean, obviously if you're a homeowner, you have certain responsibilities to your bank. If you're an apartment, you know, holder, you only have it to the lease the landlord if they even require that. So it, it's very easily to to be denied, I guess.

Lisa Smith (21:50):

So how do we sell a sophisticated product, financial, a financial tools product that people don't really want to buy, but how do we sell it to them and make them feel comfortable buying it? Especially if we remove that advisor out of the way that advisor has the pro of, they've got all the knowledge and all the information, but people don't necessarily want to deal with a sales advisor right off the beginning. They want to do, you know, they, they say this a lot about the millennial markets. They say this a lot about Gen Z and honestly, it was true with the boomers before. Nobody wants to look like an idiot. So you want to go and ask your questions and do your research ahead of time and then talk to somebody. You want to go in with that list of questions as an educated consumer. And I think that's where the ChatGPTs, the, the copilots, the different tools will help consumers. Where I really see a fun challenge and that we've been dealing with that distribution challenge that I mentioned is how do I now, when I know that you're going through that adventure, when you're looking up travel insurance or you're looking up home insurance, or you're looking up an insurance policy because you want to start your own business or you're going to work as a gig worker and you need some, some policies, how do I find you out there in the, in the, in the wide world of web and recommend the right policy to you? How do I find the right product mix or know what you're going on so that I can recommend the right solution to you at the right time? How do I know you're car shopping? How do I know you're getting ready to have a baby? How do I know that your kid just moved out to university and you're now teenager free? Those are all things that can trigger your financial plan and your insurance plan that should be reassessed and changed. And that's part of the challenge that I personally have been trying to dig into and take off with the catches. Every time we try to dig into that, we get bogged down in all those other things with the product design, with the interfaces that are available to us. How are we going to get the companies to give us the rates, the products, the salespeople? How do we get this to say, okay, you know what though, you're straightforward, we can handle your claim or your question or your sale digitally, but wait, no, somebody else has a different question in different situation and we need to talk to them. Or they should be talking to an advisor and direct people to the right places at the right time. It's not an easy, when you start to realize how it's not just a straight digitize the document. It's not a front end scan or a backend scan or make it digital from the get go type problem anymore. This question of connectivity that I mentioned and trying to get the system and the datas to work together is actually getting almost logarithmically worse instead of better.

Wade Erickson (24:31):

Because our connections are growing. You know, when you, when you have the, you know, before, before the internet, our connections were you know, largely predictable within certain you know, methods of communication, whether it be government data or something like that, that would trigger those kind of, you know, death events or birth events or things like that. It was a probably a fairly small subset of data that you could actually look for these events nowadays, like you said, you have multiple events within, you know, a a year, much less a lifetime, you know, to, to maybe reassess things like that. So that's a very, very interesting point. So given, given this changing market plus you have lots of competition, what kind of strategies to cause you're on the consulting side, so that means you're always on the front edge of helping companies, right? How do you stay, you know up to date and, you know you know, employ, you know, different strategies to stay on that competitive edge?

Lisa Smith (25:32):

Oh, as a CEO, especially as a woman CEO of a startup, let me tell you, it's exhausting. It's been really interesting to actually see there's some online support groups and some networking groups that are actually trying to encourage CEOs and women CEOs and tech CEOs how to battle through this. But I would say my personal solution, and, and this may or may not work for everybody, but it's networking. And I go back to some of the favorite CTOs and CIOs that I've worked with over my career, and I'm reaching out to them saying, Hey, let's have a quick chat. And we're having discussions about things like that example that I, I was just giving you about the liability and asking the questions wrong. A couple of us were brainstorming and testing chat GPT and what answers it might give us. And we just did it as a prior coffee video chat, didn't care that, you know, no makeup, no dress up, just get on a call with the CTO and brainstorm, this is my business problem. What are you proposing as the solution? What does it look like? I encourage my partner and co-founder, you know, get on with other CTOs and other networks, Hey, here's somebody from my career that you should be talking to. And he's saying, well, here's somebody from my career that you should be talking to and trying to merge, keeping me as a strategist on top of what they're actually capable of. Because again, that's been over the span of my career. That's been the really fascinating thing. As I was doing the business solutions and the business architect and, and, and getting ready to find my own company, it was how those people keep me informed of what they're capable of and what the technology is capable of. Then I can sit there and think of the ways to use it. Sometimes we think of it the other way, I'll come up with something and they have to go solve that problem. But a lot of times I've been, my personal experience is it flows the other way too because they tell me a, a capability that they've got or something they're exploring or something that's been interesting them and they've been tinkering with it. I can sit back and say, but wait a minute. I have a use case for that. Oh, well wait a minute. I have an opportunity for that. Well, wait a minute. Why is this even interesting? I don't understand. And they couldn't explain it to me. And I will say I have been very blessed over my career working with some very fantastic startup CTOs, CIOs working with some very fantastic insurance company, CTOs, CIOs, and how do we pull that all together? And conferences are great, but I would say there's a habit in a lot of conferences to go and get into the party side. Yes, we need to have a little fun and let loose. There's a chance sometimes to just go and sit and listen to the topics and educate ourselves. We need to do that. But the bigger thing is talk to the person sitting next to you because they're there for the same reason. Find out why, what motivated them. And that leads to some really great of these networking conversations and how you expand it.

Wade Erickson (28:31):

Great. So this is, you know, as we're approaching the top of the hour I like to pivot to pivot the already. Yes. They're very fast. I like to pivot towards kind of your personal story a little bit and 'cause we have a lot of people watching it, you know, want to get into the c-suite, want to, you know, grow their career and you know, every time I ask the question, you know, how did you become a CEO? What was that, you know, change that allowed you to make that jump? 'cause It's not easy all the time within a company and you know, it's always different for everybody. So, so tell me a bit, I saw in your history, you, you, you worked in sales, you worked in client relationships, you're currently, and then you a value consultant manager, which sounds like that business architect side of things, right? Sorry about that. And then you had the courage to go out and start your own business. That's not always easy. So tell me a little bit about that journey and what, what made you think, yes, I want to start this company and be the CEO and be in charge?

Lisa Smith (29:36):

It's a really set of funny stories. So way back early in my career, I actually started on the life and health side and then I ended up spending more time on the property and casualty side of my career. But because I got that exposure to life and health in the early days, I developed a lot of really good financial habits. Live below your means, plan your savings, save your plan all those great things. And I have a very supportive family and we had a very tight knit family. I planned everything around when my daughter, we only had the one child, but when my daughter turned 17 and had to make the decision to go to university I literally had the mortgages time, the life insurance policies paid up, her education fund paid up. I had everything sitting back and I could sit back and say, okay, now what? And she turned around and said, I'm moving three provinces, four provinces away and a time zone away to go to university. And I said, okay, looks like you're not coming home on the weekends or staying at home. And so we moved out of the big city, moved back to our small town roots, and I was all set to retire. I was doing some consulting on the side still, and I was trying to help a company in Singapore that was doing embedded insurance and digital insurance. And I reached out to a former CIO that I worked with and said, I need some mentoring help. This company needs some help. I, I think I know what they need to do, but I, I need the mentoring. How do I up my consulting game to tell this c-suite that I think they're selling their product wrong in North America? \And it was really amazing. You know, this, this, this gentleman that I worked for years ago came back to me and said, yeah, you know, you were a respected, trusted partner of our team at the time. Glad you reconnected. Let me see what I can do to help. Do you mind if I have some conversations with them? Absolutely. We set up those conversations, they went through the steps. He came back to me and said, you're right. And they're unfortunately not really prepared to listen. I think you could up your consulting game and do more, but the reality is why don't I just invest in you? And somebody else having that confidence in me at that time to say, look, I saw you before. I see what you're doing now. I see your vision. I see how you're trying to help them, but why aren't you just doing this yourself? It hit me in the comical good way. Like a sledgehammer. Well, yeah, right. Why am I not doing this? You know I'm ready to retire, but I'm leaving my industry exactly the way it was when I started. And maybe that's not the best way to leave my industry, is to take my 30 years of sales solution and consulting connectivity experience and walk away because that's not an AI database. You know, that knowledge, that, that experience, that that set of, of things. I've been blessed. I've traveled all across Canada, the us parts of the EU, UK learning insurance models and insurance systems and different product types, and I'm prepared to retire and walk away. And that's not a good, that's not a good thing for the industry. So yeah, my story was all of a sudden somebody had confidence in me and kind of inspired me and my family turned around and said, yeah, why don't you do this? You need a hobby. You need something to do. They think I'm too young to retire. Honestly, I thought I was a very good age to retire, but we can all debate that one offline. But the reality was why don't you do something for your industry?

Wade Erickson (33:17):

And I, and I think that that is probably often a trend that I see is that to take on and say, I want to do this. It's moved from not always just the focus on money to the purpose and, and finding that, just like you said, I have things to assist beyond just the money. I could retire, I could be happy with what I have, but I have more to give. And so and a lot of people are, and nothing wrong with retiring at an early age. I have family that I'm jealous that they are retired and stuff, but at the same time, I, I've had startups and I still have visions for other things I want to do. And, and as long as my brain's firing on most of the cylinders, cylinders, you know, I, I want to tackle some of those things and provide a, a better place than what I, you know, leave, leave the place better than when I came and, and the best I can do. And I think that's a common thread. And that's what takes the courage. And like you said, somebody believed in you. So some have, some have the, the self-belief. And some have to be shown that, you know but either way, as long as the confidence comes, and I've had a plenty of stories where I didn't believe in myself and my people did, and I absolutely came out great on the other side and it taught me get rid of that self-doubt. You know,

Lisa Smith (34:44):

You know what? Because self-doubt is a killer. But we, we got to understand we're not expected to know it all. We're not expected to do it all. What we are expected is to learn and share. And I've always felt that that's been my personal strength. I continuously learn, as I said, from those CIOs, CTOs, business people around me. But I've also hope that I've succeeded in paying it forward by sharing it up and down. You know, here I was speaking at my alma mater a couple weeks ago sharing my, my experience with them and, and I think to some degree they were flattering me, but to some degree they were, they were quite honest when they said, yeah, we, we learned something from your speech, you know, this is, this was great to hear. And it's that pay it forward moment, you know it's not just by paying for the coffee for the guy behind you. It's not letting that knowledge that some of us have exit at the door. It's paying it forward, sharing it forward and understanding why, why did we do this disruption and not that disruption? Why did we support this technology and not that technology? Why did we support this business process and not that business process? And that information isn't in databases, those decision trees are, are in the retiring c-suites head. It's those of us that were VPs and directors and project managers that now have that knowledge that need to share it with the teams below us. Yes, they're coming in with great ideas. They're growing up with this technology that we have to struggle to keep up with as, as leaders. You know as CEOs we're told, well, AI's going to do this and that for you. You need to be in there, you need to have that. But we need to know what they're going to do with that tool. We need to provide them with the steady helm of you can't throw away what we have known what we do know for a hope of ai. AI is going to do a lot of great things for us, but we've got to give it the framework. We've got to layer that expertise on it. We've got to layer a little bit of reality on it. And I think that's the thing. I didn't want to see leave in my case. And, and a lot of my cohorts, my co people, co-founders that are joining me, that's the same thing. They we're all of a certain age of a certain vintage. We've got a certain amount of experience, but none of us are done learning and I don't think any of us are done sharing.

Wade Erickson (37:03):

Great. That is a great answer, thank you for that. Alright, well I think we're at the end of the hour. I wanted to announce next week's guest and then of course final thank you to you. So next week we have Neil Kar, he's co-founder and CFO of NV Payments. It's a virtual banking and blockchain company that's bringing innovation to international trade transactions, banking and infrastructure. And that is, and he's out of a couple of Netherlands, Germany. And so we're going to have a foreign offshore, I should say for the US yes. Next week. So that, looking forward to that. And so it'll be just look for the next week's episodes to get the exact day and it typically the time's 9:30 AM. Alright, well thank you so much Lisa, for your time today sharing your expertise and your knowledge. Time flies. I'm sure we can talk for another hour on this topic. But appreciate the time you've given us.

Lisa Smith (38:03):

Thank you. It was a pleasure.

Wade Erickson (38:04):

Alright, you have a good day. Oh, it's May 1st. It looks like May 1st is the show next week. We just Carlos, just let me know. Alright, thank you very much and everybody else have a great rest of your week.